We studied whether a melanoma survivor-centered intervention was more effective than materials available to the general public in increasing children’s sun protection.
In a randomized controlled trial, melanoma survivors (n=340) who had a child ≤12 years received a targeted sun protection intervention (DVD and booklets) or standard education. Primary outcomes were children’s sunburns, children’s sun protection, and survivors’ psychosocial factors at baseline and postintervention (1 and 4 months).
The intervention increased children’s sunscreen reapplication at 1 month (P = 0.002) and use of wide-brimmed hats at 4 months (P = 0.045). There were no effects on other behaviors or sunburns. The intervention improved survivors’ hats/clothing self-efficacy at both follow-up assessments (P = 0.026, 0.009). At 4 months, the intervention improved survivors’ clothing intentions (P = 0.029), knowledge (P = 0.010), and outcome expectations for hats (P = 0.002) and clothing (P = 0.037). Children’s sun protection increased with survivors’ intervention use. The intervention was less effective in survivors who were female or who had a family history, older children, or children with higher baseline sun protection scores.
A melanoma survivor-centered sun protection intervention can improve some child and survivor outcomes. The intervention may be more effective in survivors who have younger children or less experience with sun protection. Intervention delivery must be enhanced to maximize use.
This is the first study to examine a sun protection intervention for children of melanoma survivors. Findings will guide interventions for this important population at increased melanoma risk.
Melanoma; Prevention & Control; Survivors; Child; Health Behavior
Despite extensive research on the topic, glioma etiology remains largely unknown. Exploration of potential interactions between single-nucleotide polymorphisms (SNPs) of immune genes is a promising new area of glioma research. The case-only study design is a powerful and efficient design for exploring possible multiplicative interactions between factors that are independent of one another. The purpose of our study was to use this exploratory design to identify potential pair wise SNP-SNP interactions from genes involved in several different immune-related pathways for investigation in future studies.
The study population consisted of two case groups: 1224 histological-confirmed, non-Hispanic white glioma cases from the U.S. and a validation population of 634 glioma cases from the U.K. Polytomous logistic regression, in which one SNP was coded as the outcome and the other SNP was included as the exposure, was utilized to calculate the odds ratios of the likelihood of cases simultaneously having the variant alleles of two different SNPs. Potential interactions were examined only between SNPs located in different genes or chromosomes.
Using this data-mining strategy, we found 396 significant SNP-SNP interactions among polymorphisms of immune-related genes that were present in both the U.S. and U.K. study populations.
This exploratory study was conducted for the purpose of hypothesis generation, and thus has provided several new hypotheses that can be tested using traditional case-control study designs to obtain estimates of risk.
This is the first study, to our knowledge, to take this novel approach to identifying SNP-SNP interactions relevant to glioma etiology.
Several national healthcare-based smoking cessation initiatives have been recommended to facilitate the delivery of evidence-based treatments such as those delivered by quitlines. The most notable examples are the 5 A’s (i.e., Ask, Advise, Assess, Assist, Arrange) and Ask Advise Refer (AAR). Unfortunately, primary care referrals to quitlines are low and the majority of smokers referred fail to call for assistance. This study evaluated a new approach -Ask Advise Connect (AAC) - designed to address barriers to linking smokers with treatment.
A pair-matched-two-treatment arm group-randomized design in 10 family practice clinics in the Houston, TX metropolitan area was utilized. Five clinics were randomized to AAC (intervention) and five were randomized to AAR (control). In both conditions, clinic staff were trained to assess and record the smoking status of all patients at all visits in the electronic health record (EHR), and smokers were given brief advice to quit. In AAC, the names and phone numbers of smokers who agreed to be connected were sent electronically to the Quitline daily, and patients were proactively called by the Quitline within 48 hours. In AAR, smokers were offered a Quitline referral card and encouraged to call on their own. All data were collected between February and December 2011. The primary outcome – impact – was based on the RE-AIM conceptual framework. Impact was defined as the proportion of all identified smokers that enrolled in treatment.
In AAC, 7.8% of all identified smokers enrolled in treatment versus 0.6% in AAR (t(4)=9.19, p=0.0008, OR=11.60 (95% CI 5.53-24.32), a 13-fold increase in the proportion of smokers enrolling in treatment in AAC compared to AAR.
The system changes implemented in AAC could be adopted broadly by other healthcare systems and AAC has tremendous potential to reduce tobacco-related morbidity and mortality.
We propose a two-step model-based approach, with correction for ascertainment, to linkage analysis of a binary trait with variable age of onset and apply it to a set of multiplex pedigrees segregating for adult glioma.
First, we fit segregation models by formulating the likelihood for a person to have a bivariate phenotype, affection status and age of onset, along with other covariates, and from these we estimate population trait allele frequencies and penetrance parameters as a function of age (N=281 multiplex glioma pedigrees). Second, the best fitting models are used as trait models in multipoint linkage analysis (N=74 informative multiplex glioma pedigrees). To correct for ascertainment, a prevalence constraint is used in the likelihood of the segregation models for all 281 pedigrees. Then the trait allele frequencies are re-estimated for the pedigree founders of the subset of 74 pedigrees chosen for linkage analysis.
Using the best fitting segregation models in model-based multipoint linkage analysis, we identified two separate peaks on chromosome 17; the first agreed with a region identified by Shete et al. who used model-free affected-only linkage analysis, but with a narrowed peak: and the second agreed with a second region they found but had a larger maximum log of the odds (LOD).
Our approach has the advantage of not requiring markers to be in linkage equilibrium unless the minor allele frequency is small (markers which tend to be uninformative for linkage), and of using more of the available information for LOD-based linkage analysis.
Glioma; model-based linkage; segregation; age of onset; prevalence constraint
A genome-wide association (GWA) study is usually designed as a case-control study, where the presence and absence of the primary disease defines the cases and controls, respectively. Using the existing data from GWA studies, investigators are also trying to identify the association between genetic variants and secondary phenotypes, which are defined as traits associated with the primary disease. However, recent studies have shown that bias arises in the estimation of marker-secondary phenotype association using originally collected data. We recently proposed a bias correction approach to accurately estimate the odds ratio (OR) for marker-secondary phenotype association. In this communication, we further investigated whether our bias correction approach is robust for a scenario involving the interactive effect of the secondary phenotype and genetic variants on the primary disease. We found that in such a scenario, our bias correction approach also provides an accurate estimation of OR for marker-secondary phenotype association. We investigated accuracy of our approach using simulation studies and showed that the approach better controlled for type I errors than the existing approaches. We also applied our bias correction approach to the real data analysis of association between an N-acetyltransferase gene, NAT2, and smoking on the basis of colorectal cancer data.
odds ratio; bias; secondary phenotype; SNP; genome-wide association study; frequency-matched study design
Renal cell carcinoma (RCC) accounts for ~4% of all human malignancies and is the 9th leading cause of male cancer death in the United States. The purpose of this study was to determine the effect of variation within microRNA (miRNA) binding sites of genes in the VHL-HIF1α pathway on RCC risk. We identified 429 miRNA binding site single nucleotide polymorphisms (SNPs) in 102 pathway genes and assessed 53 tagging-SNPs for 31 of these genes for risk in a case-control study consisting of 894 RCC cases and 1,516 controls. Results showed that five SNPs were significantly associated with RCC risk. The most significant finding was rs743409 in MAPK1. Under the additive model, the variant was associated with a 10% risk reduction (OR: 0.90, 95% CI, 0.77-0.98). Other significant findings were for SNPs in CDCP1, TFRC, and DEC1. Cumulative effects analysis showed that subjects carrying four or five unfavorable genotypes had a 2.14-fold increase in risk (95% CI, 1.03-4.43, P = 0.04) than those with no unfavorable genotypes. Potential higher-order gene-gene interactions were identified and categorized subjects into different risk groups. The OR of the high-risk group defined by two SNPs: CDCP1:rs6773576 (GG) and DEC1:rs10982724 (GG) was 4.46-times higher than that of low-risk reference group (95% CI, 1.31-15.08). Overall, our study provides the first evidence supporting a connection between miRNA binding site SNPs within the VHL-HIF1α pathway and RCC risk. These novel genetic risk factors might help identify individuals at high risk to enable detection of tumors at an early, curable stage.
VHL-HIF1α pathway; microRNA; renal cell carcinoma
A compromised brain reward system has been postulated as a key feature of drug dependence. We examined whether several polymorphisms of genes found to regulate nicotinic acetylcholine receptor (nAChR) and dopamine expression were related to an intrinsic reward sensitivity (IRS) deficit we previously identified among a subgroup of smokers using event-related potentials (ERPs). We examined genetic polymorphisms within the CHRNA5-A3-B4 gene cluster (CHRNA3 rs578776, CHRNA5 rs16969968, LOC123688 rs8034191, and CHRNA3 rs1051730), the ANKK1 gene (rs1800497), and the D2 dopamine receptor gene (DRD2 rs1079597, DRD2 rs1799732) from 104 smokers of European ancestry in a smoking cessation trial. Prior to treatment, we recorded ERPs evoked by emotional (both pleasant and unpleasant), neutral, and cigarette-related pictures. Smokers were assigned to two groups (IRS+/IRS−) based on the amplitude of the late positive potential (LPP) component to the pictures, a neural marker of motivational salience. Smokers (n = 42) with blunted brain responses to intrinsically rewarding (pleasant) pictures and enhanced responses to cigarette pictures were assigned to the IRS− group, while smokers (n = 62) with the opposite pattern of LPP responding were assigned to the IRS+ group. Carriers of the protective minor T allele (T/T, C/T) of the CHRNA3 rs578776 were less likely to be members of the IRS− group than those homozygous for the at-risk C allele (C/C). The CHRNA3 rs578776 polymorphism did not differ on questionnaires of nicotine dependence, depressed mood, or trait affective disposition and did not predict abstinence at 6 months after the quit date. These results suggest that polymorphisms of genes influencing nAChR expression are related to an endophenotype of reward sensitivity in smokers.
nAChR; DRD2; nicotine; reward sensitivity; ERP; LPP; smoking cessation; genetics
The risk of glioma has consistently been shown to be increased two-fold in relatives of patients with primary brain tumors (PBT). A recent genome-wide linkage study of glioma families provided evidence for a disease locus on 17q12-21.32, with the possibility of four additional risk loci at 6p22.3, 12p13.33-12.1, 17q22-23.2, and 18q23.
To identify the underlying genetic variants responsible for the linkage signals, we compared the genotype frequencies of 5,122 SNPs mapping to these five regions in 88 glioma cases with and 1,100 cases without a family history of PBT (discovery study). An additional series of 84 familial and 903 non-familial cases were used to replicate associations.
In the discovery study, 12 SNPs showed significant associations with family history of PBT (P < 0.001). In the replication study, two of the 12 SNPs were confirmed: 12p13.33-12.1 PRMT8 rs17780102 (P = 0.031) and 17q12-21.32 SPOP rs650461 (P = 0.025). In the combined analysis of discovery and replication studies, the strongest associations were attained at four SNPs: 12p13.33-12.1 PRMT8 rs17780102 (P = 0.0001), SOX5 rs7305773 (P = 0.0001) and STKY1 rs2418087 (P = 0.0003), and 17q12-21.32 SPOP rs6504618 (P = 0.0006). Further, a significant gene-dosage effect was found for increased risk of family history of PBT with these four SNPs in the combined data set (Ptrend < 1.0 ×10−8).
The results support the linkage finding that some loci in the 12p13.33-12.1 and 17q12-q21.32 may contribute to gliomagenesis and suggest potential target genes underscoring linkage signals.
Association; Polymorphisms; Glioma; Family history of primary brain tumor; Linkage analysis
A genetic predisposition for thoracic aortic aneurysms and dissections (TAAD) can be inherited in an autosomal dominant manner with decreased penetrance and variable expression. Four genes identified to date for familial TAAD account for approximately 20% of the heritable predisposition. In a cohort of 514 families with two or more members with presumed autosomal dominant TAAD, 48 (9.3%) families have one or more members who were at 50% risk to inherit the presumptive gene causing TAAD had an intracranial vascular event. In these families, gender is significantly associated with disease presentation (p <0.001), with intracranial events being more common in women (65.4%) while TAAD events occurred more in men (64.2%,). Twenty-nine of these families had intracranial aneurysms (ICA) that could not be designated as saccular or fusiform due to incomplete data. TGFBR1, TGFBR2, and ACTA2 mutations were found in 4 families with TAAD and predominantly fusiform ICAs. In 15 families, of which 14 tested negative for 3 known TAAD genes, 17 family members who were at risk for inheriting TAAD had saccular ICAs. In 2 families, women who harbored the genetic mutation causing TAAD had ICAs. In 2 additional families, intracranial, thoracic and abdominal aortic aneurysms were observed. This study documents the autosomal dominant inheritance of TAADs with saccular ICAs, a previously recognized association that has not been adequately characterized as heritable.I these families, routine cerebral and aortic imaging for at risk members could prove beneficial for timely medical and surgical management to prevent a cerebral hemorrhage or aortic dissection.
thoracic aortic aneurysm; aortic dissection; fusiform intracranial aneurysms; saccular intracranial aneurysms; abdominal aortic aneurysm; genetic counseling
Thoracic aortic aneurysms leading to acute aortic dissections (TAAD) are the major diseases that affect the thoracic aorta. Approximately 20% of patients with TAAD have a family history of TAAD, and these patients present younger with more rapidly enlarging aneurysms than patients without a family history of aortic disease.
Methods and Results
A large family with multiple members with TAAD inherited in an autosomal dominant manner was identified. The ascending aortic aneurysms were associated with slow enlargement, a low risk of dissection, and decreased penetrance in women. Genome-wide linkage analysis was performed and a novel locus on chromosome 12 was identified for the mutant gene causing disease in this family. Of the 12 male members who carry the disease-linked microsatellite haplotype, nine had ascending aortic aneurysms with an average diameter of 4.7 cm and average age of 55 years (age range, 32-76) at the time of diagnosis; only one individual had progressed to acute aortic dissection and no other members with aortic dissections were identified. Women harboring the disease-linked haplotype did not have thoracic aortic disease, including an 84 year old woman. Sequencing of 9 genes within the critical interval at the chromosome 12 locus did not identify the mutant gene.
Mapping a locus for ascending thoracic aortic aneurysms associated with a low risk of aortic dissection supports our hypothesis that genes leading to familial disease can be associated with less aggressive thoracic aortic disease.
acute aortic dissection genes; aneurysm; genome-wide analysis; mapping; risk prediction
Rare variants have increasingly been cited as major contributors in the disease etiology of several complex disorders. Recently, several approaches have been proposed for analyzing the association of rare variants with disease. These approaches include collapsing rare variants, summing rare variant test statistics within a particular locus to improve power, and selecting a subset of rare variants for association testing, e.g., the step-up approach. We found that (a) if the variants being pooled are in linkage disequilibrium, the standard step-up method of selecting the best subset of variants results in loss of power compared to a model that pools all rare variants and (b) if the variants are in linkage equilibrium, performing a subset selection using step-based selection methods results in a gain of power of association compared to a model that pools all rare variants. Therefore, we propose an approach to selecting the best subset of variants to include in the model that is based on the linkage disequilibrium pattern among the rare variants. The proposed linkage disequilibrium–based variant selection model is flexible and borrows strength from the model that pools all rare variants when the rare variants are in linkage disequilibrium and from step-based selection methods when the variants are in linkage equilibrium. We performed simulations under three different realistic scenarios based on: (1) the HapMap3 dataset of the DRD2 gene, and CHRNA3/A5/B4 gene cluster (2) the block structure of linkage disequilibrium, and (3) linkage equilibrium. We proposed a permutation-based approach to control the type 1 error rate. The power comparisons after controlling the type 1 error show that the proposed linkage disequilibrium–based subset selection approach is an attractive alternative method for subset selection of rare variants.
Genome-wide association studies have identified variants on chromosome 15q25.1 that increase the risks of both lung cancer and nicotine dependence and associated smoking behavior. However, there remains debate as to whether the association with lung cancer is direct or is mediated by pathways related to smoking behavior. Here, the authors apply a novel method for mediation analysis, allowing for gene-environment interaction, to a lung cancer case-control study (1992–2004) conducted at Massachusetts General Hospital using 2 single nucleotide polymorphisms, rs8034191 and rs1051730, on 15q25.1. The results are validated using data from 3 other lung cancer studies. Tests for additive interaction (P = 2 × 10−10 and P = 1 × 10−9) and multiplicative interaction (P = 0.01 and P = 0.01) were significant. Pooled analyses yielded a direct-effect odds ratio of 1.26 (95% confidence interval (CI): 1.19, 1.33; P = 2 × 10−15) for rs8034191 and an indirect-effect odds ratio of 1.01 (95% CI: 1.00, 1.01; P = 0.09); the proportion of increased risk mediated by smoking was 3.2%. For rs1051730, direct- and indirect-effect odds ratios were 1.26 (95% CI: 1.19, 1.33; P = 1 × 10−15) and 1.00 (95% CI: 0.99, 1.01; P = 0.22), respectively, with a proportion mediated of 2.3%. Adjustment for measurement error in smoking behavior allowing up to 75% measurement error increased the proportions mediated to 12.5% and 9.2%, respectively. These analyses indicate that the association of the variants with lung cancer operates primarily through other pathways.
gene-environment interaction; lung neoplasms; mediation; pathway analysis; smoking
Breast cancer diagnosis and treatment can have a profound influence on a woman's physical, psychosocial, and overall well-being. We examined the prevalence of depressive symptoms and its association with health-related quality of life (HRQOL) in women who are survivors of breast cancer. We also assessed if factors, including metastasis, cancer recurrence, diagnosis of new primary cancers, and comorbid conditions, are associated with depressive symptoms.
The Patient Health Questionnaire (PHQ-8) and European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 were mailed to assess depressive symptoms and HRQOL, respectively, in breast cancer patients who received cancer treatment in a large tertiary cancer center.
Two hundred forty patients participated (56% response rate and 6–13 years since treatment). The mean score on the PHQ-8 scale was 4 points (standard deviation [SD] 4.8, median 2.0). Sixteen percent had PHQ-8 score ≥10 and were categorized as depressed. Depression was inversely associated with HRQOL subscales for functioning, financial, and global health and positively associated with symptoms. Logistic regression showed that younger age (odds ratio [OR] age in years 0.92, 95% confidence interval [CI] 0.86- 0.99, p<0.02), rheumatoid arthritis (OR 8.4, 95%CI 1.3-57.4, p<0.03), and years from treatment (OR 0.70, 95% CI 0.46-0.99, p<0.05) were significant correlates of depression.
Depression is a significant health concern for breast cancer survivors and is associated with lower HRQOL. The results suggest the need to monitor women with breast cancer for depression and provide resources for treating depression during the survival period.
Effective management of symptoms in cancer patients requires early intervention. We assessed whether the timing of referral to the Supportive Care Center (SCC) and symptom burden outcome varied by race or ethnicity in lung cancer patients who had been seen at a tertiary cancer center.
Non-Hispanic white (n=752), Hispanic (n=111) and non-Hispanic black (n=117) patients with non-small cell lung cancer comprised our sample. Data on sociodemographic factors, stage of disease, comorbid conditions, and symptom severity (pain, depressed mood, fatigue) served as potential predictor variables.
While the mean time (15 months; median=7 months) from initial presentation at the cancer center to referral to the SCC did not vary by race or ethnicity, we found that Hispanics and non-Hispanic blacks had higher symptom burden when they first presented at the cancer center than non-Hispanic whites. Severe pain, depressed mood, and fatigue were significant predictors for early referral (< 7 months) of non-Hispanic whites, but only severe fatigue (P < 0.05) was predictive of early referral for Hispanics and non-Hispanic blacks. Furthermore, while the proportion of non-Hispanic white patients reporting severe pain, depressed mood, and fatigue significantly decreased (P < 0.001) at first follow-up visit after referral to the SCC; among Hispanics, improvement was only observed for depressed mood. No improvement in any of these symptoms was observed for non-Hispanic blacks.
While the timing of referral to supportive services did not vary by race, disparities in symptom burden outcomes persist. Additional studies are needed to validate our findings.
Folate metabolism, with its importance to DNA repair, provides a promising region for genetic investigation of lung cancer risk. This project investigates genes (MTHFR, MTR, MTRR, CBS, SHMT1, TYMS), folate metabolism related nutrients (B vitamins, methionine, choline, and betaine) and their gene-nutrient interactions.
We analyzed 115 tag single nucleotide polymorphisms (SNPs) and 15 nutrients from 1239 and 1692 non-Hispanic white, histologically-confirmed lung cancer cases and controls, respectively, using stochastic search variable selection (a Bayesian model averaging approach). Analyses were stratified by current, former, and never smoking status.
Rs6893114 in MTRR (odds ratio [OR] = 2.10; 95% credible interval [CI]: 1.20–3.48) and alcohol (drinkers vs. non-drinkers, OR = 0.48; 95% CI: 0.26–0.84) were associated with lung cancer risk in current smokers. Rs13170530 in MTRR (OR = 1.70; 95% CI: 1.10–2.87) and two SNP*nutrient interactions [betaine*rs2658161 (OR = 0.42; 95% CI: 0.19–0.88) and betaine*rs16948305 (OR = 0.54; 95% CI: 0.30–0.91)] were associated with lung cancer risk in former smokers. SNPs in MTRR (rs13162612; OR = 0.25; 95% CI: 0.11–0.58; rs10512948; OR = 0.61; 95% CI: 0.41–0.90; rs2924471; OR = 3.31; 95% CI: 1.66–6.59), and MTHFR (rs9651118; OR = 0.63; 95% CI: 0.43–0.95) and three SNP*nutrient interactions (choline*rs10475407; OR = 1.62; 95% CI: 1.11–2.42; choline*rs11134290; OR = 0.51; 95% CI: 0.27–0.92; and riboflavin*rs8767412; OR = 0.40; 95% CI: 0.15–0.95) were associated with lung cancer risk in never smokers.
This study identified possible nutrient and genetic factors related to folate metabolism associated with lung cancer risk, which could potentially lead to nutritional interventions tailored by smoking status to reduce lung cancer risk.
We, and others, have shown that experimenting with cigarettes is a function of both non-genetic and genetic factors. In this analysis we ask: how much of the total risk of experimenting with cigarettes, among those who had not experimented with cigarettes when they enrolled in a prospective cohort, is attributable to genetic factors and to non-genetic factors?
Participants (N = 1,118 Mexican origin youth), recruited from a large population-based cohort study in Houston, Texas, provided prospective data on cigarette experimentation over three years. Non-genetic data were elicited twice – baseline and follow-up. Participants were genotyped for 672 functional and tagging variants in the dopamine, serotonin and opioid pathways.
In the overall model, the adjusted combined non-genetic PAF was 71.2% and the adjusted combined genetic PAF was 58.5%. Among committed never smokers the adjusted combined non-genetic PAF was 67.0% and the adjusted combined genetic PAF was 53.5%. However, among cognitively susceptible youth, the adjusted combined non-genetic PAF was 52.0% and the adjusted combined genetic PAF was 68.4%.
Our results suggest there may be differences in genotypes between youth who think they will try cigarettes in the future compared to their peers who think they will not and underscore the possibility that the relative influence of genetic vs. non-genetic factors on the uptake of smoking may vary between these two groups of youth.
A clearer understanding of the relative role of genetic vs. non-genetic factors in the uptake of smoking may have implications for the design of prevention programs.
Growing evidence suggests that single nucleotide polymorphisms (SNPs) in nucleotide excision repair (NER) pathway genes play an important role in bladder cancer etiology. However, only a limited number of genes and variations in this pathway have been evaluated to date.
In this study, we applied a comprehensive pathway-based approach to assess the effects of 207 tagging and potentially functional SNPs in 26 NER genes on bladder cancer risk using a large case-control study consisting of 803 bladder cancer cases and 803 controls.
A total of 17 SNPs were significantly associated with altered bladder cancer risk at P<0.05, of which 7 SNPs retained noteworthiness after assessed by a Bayesian approach for the probability of false discovery. The most noteworthy SNP was rs11132186 in ING2 gene. Compared to the major allele-containing genotypes, the odds ratio (OR) was 0.52 (95% confidence interval [CI] 0.32–0.83, P = 0.005) for the homozygous variant genotype. Three additional ING2 variants also exhibited significant associations with bladder cancer risk. Significant gene-smoking interactions were observed for three of the top 17 SNPs. Furthermore, through an exploratory classification and regression tree (CART) analysis, we identified potential gene-gene interactions.
We conducted a large association study of NER pathway with bladder cancer risk and identified several novel predisposition variants. We identified potential gene-gene and gene-environment interactions in modulating bladder cancer risk. Our results reinforce the importance of a comprehensive pathway-focused and tagging SNP-based candidate gene approach to identify low-penetrance cancer susceptibility loci.
bladder cancer; genetic susceptibility; nucleotide excision repair; SNP; gene-smoking interaction
Established psychosocial risk factors increase the risk for experimentation among Mexican-origin youth. Now we comprehensively investigate the added contribution of select polymorphisms in candidate genetic pathways associated with sensation seeking, risk taking, and smoking phenotypes to predict experimentation.
Participants, (N=1,118 Mexican origin youth) recruited from a large population-based cohort study in Houston, Texas, provided prospective data on cigarette experimentation over three years. Psychosocial data were elicited twice—baseline and final follow-up. Participants were genotyped for 672 functional and tagging variants in the dopamine, serotonin and opioid pathways.
After adjusting for gender and age, with a Bayesian False Discovery Probability set at 0.8 and prior probability of 0.05, six gene variants were significantly associated with risk of experimentation. After controlling for established risk factors, multivariable analyses revealed that participants with six or more risk alleles were 2.25 (95%CI: 1.62–3.13) times more likely to have experimented since baseline compared to participants with five or fewer. Among committed never smokers (N=872), three genes (OPRM1, SNAP25, HTR1B) were associated with experimentation as were all psychosocial factors. Among susceptible youth (N=246) older age at baseline, living with a smoker, and three different genes (HTR2A, DRD2, SLC6A3) predicted experimentation.
Our findings, which have implications for development of culturally-specific interventions, need to be validated in other ethnic groups.
These results suggest that variations in select genes interact with a cognitive predisposition toward smoking. In susceptible adolescents, the impact of the genetic variants appears to be larger compared to committed never smokers.
Hypersensitivity to radiation exposure has been suggested to be a risk factor for the development of breast cancer. In this case–control study of 515 young women (≤55 years) with newly diagnosed sporadic breast cancer and 402 cancer-free controls, we examined the radiosensitivity as measured by the frequency of chromatid breaks induced by gamma-radiation exposure in the G2 phase of phytohemagglutinin-stimulated and short-term cultured fresh lymphocytes. We found that the average chromatid breaks per cell from 50 well-spread metaphases were statistically significantly higher in 403 non-Hispanic White breast cancer patients (0.52 ± 0.22) than that in 281 non-Hispanic White controls (0.44 ± 0.16) (P value < 0.001), and in 60 Mexican American breast cancer patients (0.52 ± 0.19) than that in 65 Mexican American controls (0.44 ± 0.16) (P value = 0.021), but the difference was not significant in African Americans (52 cases [0.45 ± 0.16] versus 56 controls [0.47 ± 0.16], P = 0.651). The frequency of chromatid breaks per cell above the median of control subjects was associated with two-fold increased risk for breast cancer in non-Hispanic Whites and Mexican Americans. A dose–response relationship was evident between radiosensitivity and risk for breast cancer (Ptrend < 0.001) in these two ethnic groups. We concluded that gamma-ray-induced mutagen sensitivity may play a role in susceptibility to breast cancer in young non-Hispanic White and Mexican American women.
Radiation; Chromosomal instability; Breast neoplasm; Molecular epidemiology
Gliomas, which generally have a poor prognosis, are the most common primary malignant brain tumors in adults. Recent genome-wide association studies have demonstrated that inherited susceptibility plays a role in the development of glioma. Although first-degree relatives of patients exhibit a two-fold increased risk of glioma, the search for susceptibility loci in familial forms of the disease has been challenging because the disease is relatively rare, fatal, and heterogeneous, making it difficult to collect sufficient biosamples from families for statistical power. To address this challenge, the Genetic Epidemiology of Glioma International Consortium (Gliogene) was formed to collect DNA samples from families with two or more cases of histologically confirmed glioma. In this study, we present results obtained from 46 U.S. families in which multipoint linkage analyses were undertaken using nonparametric (model-free) methods. After removal of high linkage disequilibrium SNPs, we obtained a maximum nonparametric linkage score (NPL) of 3.39 (P=0.0005) at 17q12–21.32 and the Z-score of 4.20 (P=0.000007). To replicate our findings, we genotyped 29 independent U.S. families and obtained a maximum NPL score of 1.26 (P=0.008) and the Z-score of 1.47 (P=0.035). Accounting for the genetic heterogeneity using the ordered subset analysis approach, the combined analyses of 75 families resulted in a maximum NPL score of 3.81 (P=0.00001). The genomic regions we have implicated in this study may offer novel insights into glioma susceptibility, focusing future work to identify genes that cause familial glioma.
Glioma; family studies; linkage; haplotype pattern; NPL
We recently proposed a bias correction approach to evaluate accurate estimation of the odds ratio (OR) of genetic variants associated with a secondary phenotype, in which the secondary phenotype is associated with the primary disease, based on the original case-control data collected for the purpose of studying the primary disease. As reported in this communication, we further investigated the type I error probabilities and powers of the proposed approach, and compared the results to those obtained from logistic regression analysis (with or without adjustment for the primary disease status). We performed a simulation study based on a frequency-matching case-control study with respect to the secondary phenotype of interest. We examined the empirical distribution of the natural logarithm of the corrected OR obtained from the bias correction approach and found it to be normally distributed under the null hypothesis. On the basis of the simulation study results, we found that the logistic regression approaches that adjust or do not adjust for the primary disease status had low power for detecting secondary phenotype associated variants and highly inflated type I error probabilities, whereas our approach was more powerful for identifying the SNP-secondary phenotype associations and had better-controlled type I error probabilities.
Odds ratio; bias; type I error; power; secondary phenotype; frequency-matched study; SNP; genome-wide association study
A mediation model explores the direct and indirect effects between an independent variable and a dependent variable by including other variables (or mediators). Mediation analysis has recently been used to dissect the direct and indirect effects of genetic variants on complex diseases using case-control studies. However, bias could arise in the estimations of the genetic variant-mediator association because the presence or absence of the mediator in the study samples is not sampled following the principles of case-control study design. In this case, the mediation analysis using data from case-control studies might lead to biased estimates of coefficients and indirect effects. In this article, we investigated a multiple-mediation model involving a three-path mediating effect through two mediators using case-control study data. We propose an approach to correct bias in coefficients and provide accurate estimates of the specific indirect effects. Our approach can also be used when the original case-control study is frequency matched on one of the mediators. We employed bootstrapping to assess the significance of indirect effects. We conducted simulation studies to investigate the performance of the proposed approach, and showed that it provides more accurate estimates of the indirect effects as well as the percent mediated than standard regressions. We then applied this approach to study the mediating effects of both smoking and chronic obstructive pulmonary disease (COPD) on the association between the CHRNA5-A3 gene locus and lung cancer risk using data from a lung cancer case-control study. The results showed that the genetic variant influences lung cancer risk indirectly through all three different pathways. The percent of genetic association mediated was 18.3% through smoking alone, 30.2% through COPD alone, and 20.6% through the path including both smoking and COPD, and the total genetic variant-lung cancer association explained by the two mediators was 69.1%.
Genome-wide association (GWA) studies, where hundreds of thousands of single-nucleotide polymorphisms (SNPs) are tested simultaneously, are becoming popular for identifying disease loci for common diseases. Most commonly, a GWA study involves two stages: the first stage includes testing the association between all SNPs and the disease and the second stage includes replication of SNPs selected from the first stage to validate associations in an independent sample. The first stage is considered to be more fundamental since the second stage is contingent on the results of the first stage. Selection of SNPs from stage one for genotyping in stage two is typically based on an arbitrary threshold or controlling type I errors. These strategies can be inefficient and have potential to exclude genotyping of disease-associated SNPs in stage two. We propose an approach for selecting top SNPs that uses a strategy based on the false-negative rate (FNR). Using the FNR approach, we proposed the number of SNPs that should be selected based on the observed p-values and a pre-specified multi-testing power in the first stage. We applied our method to simulated data and a GWA study of glioma (a rare form of brain tumor) data. Results from simulation and the glioma GWA indicate that the proposed approach provides an FNR-based way to select SNPs using pre-specified power.
False negative rate; SNP selection; Two-stage genome-wide association study
We previously showed that select cytokine gene polymorphisms are a significant predictor for pain reported at initial presentation in 446 white patients newly diagnosed with non–small cell lung cancer. This follow-up study explores the extent to which polymorphisms in tumor necrosis factor-α (TNF- α-308 G/A), interleukin (IL)-6 −174G/C, and IL-8 −251T/A could explain variability in pain and analgesic response among those patients (n = 140) subsequently referred for pain treatment.
Pain severity (0, no pain; 10, worst pain) was assessed at initial consultation and at follow-up visit. The total dose of opioids at the time of first-follow up visit (30 days postconsult) was converted to an equivalent dose of parenteral morphine.
Forty-one percent (57 of 140) of the patients reported severe pain (score >7/10) at initial consultation (mean, 5.5), which significantly decreased to 25% (mean, 4) at first follow-up visit (McNemar = P < 0.001). Polymorphisms in TNF and IL-6 were significantly associated with pain severity (for TNF GG, 4.12; GA, 5.38; AA, 5.50; P = 0.04) and with morphine equivalent daily dose (IL-6 GG, 69.61; GC, 73.17; CC, 181.67; P = 0.004), respectively. Adjusting for demographic and clinical variables, variant alleles in TNFα −308 G/A remained significantly associated with pain severity (b = 0.226; P = 0.036) and carriers of the IL-6 −174C/C genotypes required 4.7 times higher dose of opioids for pain relief (odds ratio, 4.7; 95% confidence interval, 1.2;15.0) relative to GG and GC genotypes.
We provide preliminary evidence of the influence of cytokine genes on pain and response to analgesia in lung cancer patients. Additional studies are needed to validate our findings. The long-term application is to tailored pain therapies.
While gliomas are the most common primary brain tumors, their etiology is largely unknown. To identify novel risk loci for glioma, we conducted genome-wide association (GWA) analysis of two case–control series from France and Germany (2269 cases and 2500 controls). Pooling these data with previously reported UK and US GWA studies provided data on 4147 glioma cases and 7435 controls genotyped for 424 460 common tagging single-nucleotide polymorphisms. Using these data, we demonstrate two statistically independent associations between glioma and rs11979158 and rs2252586, at 7p11.2 which encompasses the EGFR gene (population-corrected statistics, Pc = 7.72 × 10−8 and 2.09 × 10−8, respectively). Both associations were independent of tumor subtype, and were independent of EGFR amplification, p16INK4a deletion and IDH1 mutation status in tumors; compatible with driver effects of the variants on glioma development. These findings show that variation in 7p11.2 is a determinant of inherited glioma risk.